GenoML：基因组学的自动化机器学习
GenoML: Automated Machine Learning for Genomics
摘要：
GenoML是一个Python软件包，以开放的科学理念自动化基因组学（遗传学和多组学）的机器学习工作流程。基因组学数据需要大量的领域专业知识来清理，预处理，协调和执行数据的质量控制。此外，调整、验证和解释涉及考虑生物学以及潜在的数据汇集、协议和技术的可能限制。GenoML的使命是通过开发一个易于使用的工具，自动化完整的开发，评估和部署过程，将基因组学和临床数据的机器学习带给非专家。重点放在开放科学，使工作流程易于访问，复制，并在科学界内转移。源代码和文档可在https://genoml.com上获得。
英文摘要：
GenoML is a Python package automating machine learning workflows for genomics (genetics and multi-omics) with an open science philosophy. Genomics data require significant domain expertise to clean, pre-process, harmonize and perform quality control of the data. Furthermore, tuning, validation, and interpretation involve taking into account the biology and possibly the limitations of the underlying data collection, protocols, and technology. GenoML's mission is to bring machine learning for genomics and clinical data to non-experts by developing an easy-to-use tool that automates the full development, evaluation, and deployment process. Emphasis is put on open science to make workflows easily accessible, replicable, and transferable within the scientific community. Source code and documentation is available at https://genoml.com.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
